Research Progress in Detection Technologies for Soluble Sugars in Plants

Soluble sugars are important physiologically active substances in plants. They are not only the major products of photosynthesis and core carriers of energy metabolism, but also participate in key processes such as cellular structural construction, signal transduction, and stress-response regulation. Accurate determination of the content and composition of soluble sugars in plant tissues is of great significance for elucidating growth and development patterns, evaluating crop quality, dissecting stress-resistance mechanisms, and guiding agricultural production. With iterative advances in analytical technologies, soluble sugar detection in plants has gradually evolved from traditional chemical colorimetric methods toward instrument- and sensor-based systems characterized by higher resolution, higher throughput, miniaturization, and field deployability.

I. Traditional Chemical Colorimetric Methods

Traditional chemical colorimetric methods rely on color-forming reactions between soluble sugars and specific reagents. Absorbance is measured with a spectrophotometer and quantified using a standard curve. These methods are low-cost, simple to operate, and require minimal instrumentation, making them suitable for basic laboratories and rapid screening of large sample sets. However, their common limitations include: most outputs represent “total sugar” or “reducing sugar” rather than resolved compositions; component discrimination is limited; and results are easily affected by matrix interferences such as pigments, phenolics, and proteins. Therefore, extraction/purification and appropriate blanks are essential.

1.1 Phenol–Sulfuric Acid Method

(1) Principle

Under concentrated sulfuric acid, sugars are dehydrated to form furfural or hydroxymethylfurfural, which condense with phenol to yield an orange-yellow product with a strong absorption peak at 490 nm. Within a certain range, absorbance shows a linear relationship with total sugar content, enabling quantification of total soluble sugars.

(2) Key Workflow Notes

① Sample preparation: Grind in liquid nitrogen, extract with 80% ethanol, centrifuge, collect the supernatant, and repeat extraction if necessary before pooling.

② Color development: Add phenol to the extract, then rapidly add concentrated sulfuric acid and mix; develop color in a water bath as specified and cool.

③ Quantification: Prepare glucose standards to generate a calibration curve, calculate total sugar content, and include reagent blanks and matrix blanks to correct background.

(3) Advantages/Limitations and Applicability

① Advantages: Relatively high sensitivity, relatively stable color development, mature workflow; suitable for rapid total sugar determination across many tissue types.

② Limitations: Poor specificity—pentoses, hexoses, and some oligo-/polysaccharides may respond; cannot resolve components; concentrated sulfuric acid is highly corrosive and poses safety risks.

③ Use cases: Screening and comparative studies using “total soluble sugar” as a phenotypic indicator, as well as teaching/basic testing settings.

1.2 Anthrone–Sulfuric Acid Method

(1) Principle

Sugars are dehydrated under concentrated sulfuric acid to form furfural derivatives, which react with anthrone to produce a blue-green complex with a maximal absorption at 620 nm, used for total sugar quantification.

(2) Key Workflow Notes

① Extraction: Same ethanol-extraction concept as in 1.1; minimize pigment and protein residues as much as possible.

② Color development: Mix extract with anthrone–sulfuric acid reagent, develop color in a water bath as specified, cool, and measure absorbance at 620 nm.

③ Calculation: Quantify using a glucose standard curve; control the reading time window after color development to reduce drift.

(3) Advantages/Limitations and Applicability

① Advantages: Fast reaction; good response to common mono- and disaccharides.

② Limitations: More susceptible to pigment/protein interference; color stability is moderate; repeatability depends strongly on operational consistency.

③ Use cases: Total sugar determination and batch comparisons when the matrix is relatively “clean” or has been adequately purified.

1.3 3,5-Dinitrosalicylic Acid (DNS) Method

(1) Principle

In alkaline conditions, DNS is reduced by reducing sugars to form a brown-red product. Absorbance at 540 nm is linearly related to reducing sugar content. Non-reducing sugars (e.g., sucrose) must be acid-hydrolyzed to reducing sugars before measurement, enabling an estimated separation of reducing vs. non-reducing sugars.

(2) Key Workflow Notes

① Reducing sugar measurement: Mix extract with DNS reagent, develop color in a water bath as specified, cool, measure at 540 nm, and quantify using a glucose standard curve.

② Total sugar estimation: Acid-hydrolyze the extract, neutralize, then measure as above; “total reducing sugar after hydrolysis” minus “original reducing sugar” provides an estimate of non-reducing sugar.

③ Condition control: Color development time and temperature strongly affect results; keep them strictly consistent and include replicates and QC samples.

(3) Advantages/Limitations and Applicability

① Advantages: More selective for “reducing sugars”; can estimate reducing vs. non-reducing sugars (via hydrolysis-based calculation).

② Limitations: Not suitable for direct compositional profiling of total soluble sugars; sensitive to reaction conditions; samples rich in polyphenols or strong reductants may yield positively biased results.

③ Use cases: Studies focused on reducing sugar dynamics (e.g., glucose/fructose trends under stress) or designs requiring separation of reducing and non-reducing fractions.

II. Instrumental Analytical Technologies

Instrumental methods offer high sensitivity, high specificity, and strong component separation capability, enabling simultaneous qualitative and quantitative analysis of monosaccharides, disaccharides, and even oligosaccharides. They are well suited for mechanistic research and refined quality assessment. Key success factors include standardized sample pretreatment (extraction solvent, cleanup strategy, filtration specification), stable control of chromatographic/electrophoretic conditions, and rational construction of standards and internal-standard systems.

2.1 Chromatography

Chromatographic methods separate sugar components based on differential partitioning between stationary and mobile phases, and quantify them with detectors. They are the mainstay for compositional analysis.

2.1.1 High-Performance Liquid Chromatography (HPLC)

(1) Principle

Common schemes include amino-column HPLC (acetonitrile–water systems), separating sugars based on interactions with the stationary phase. Detectors often include refractive index detection (RID) or evaporative light scattering detection (ELSD). RID generally requires no derivatization and is straightforward; ELSD offers higher sensitivity and can accommodate gradient elution.

(2) Key Workflow Notes

① Sample preparation: Centrifuge after extraction and filter through a 0.22 µm membrane to prevent particulates/colloids from entering the system.

② Method setup: Optimize mobile-phase ratio, flow rate, column temperature, and equilibration time; RID is more demanding regarding temperature and mobile-phase stability.

③ Identification/quantification: Identify by retention time using standards; quantify by peak area/height; use internal standards when needed to correct for injection variability and drift.

(3) Advantages/Limitations and Applicability

① Advantages: Good separation and high precision; can quantify multiple components such as glucose, fructose, sucrose, and maltose in one run.

② Limitations: RID has relatively limited sensitivity and is not suitable for gradients; ELSD is more sensitive to sample cleanliness and control of volatile components.

③ Use cases: Routine multi-component quantification in research and quality testing.

2.1.2 Gas Chromatography (GC)

(1) Principle

Sugars are highly polar and non-volatile, requiring derivatization (e.g., silylation) to form volatile derivatives before separation. Detection can be FID or MS; GC–MS is particularly advantageous for complex matrices and trace-level identification.

(2) Key Workflow Notes

① Pretreatment: Concentrate and dry extracts; strict water control is required to ensure derivatization efficiency.

② Derivatization: Add derivatization reagents and react under defined conditions; temperature, time, and reagent ratios must be consistent.

③ Analysis: Use temperature programming and appropriate carrier gas parameters; identify using standards/libraries and quantify by peak area.

(3) Advantages/Limitations and Applicability

① Advantages: High separation efficiency and sensitivity; MS coupling strengthens identification and supports trace component analysis.

② Limitations: Derivatization is labor-intensive and condition-sensitive; some reagents are irritating/toxic; higher operational and safety requirements.

③ Use cases: Complex samples, trace sugars, or studies requiring stronger qualitative identification.

2.1.3 Ion Chromatography (IC)

(1) Principle

Using ion-exchange resins as stationary phases, sugars are separated based on weak dissociation and interaction differences under specific conditions, commonly with pulsed amperometric detection (PAD). PAD is highly sensitive to sugars and typically requires no derivatization, supporting high-sensitivity analysis of mono-, di-, and oligosaccharides.

(2) Key Workflow Notes

① Injection: Filter aqueous samples and inject directly; minimize salts and organic impurities to protect the column.

② Separation: Set eluent gradients, flow rate, and column temperature; ensure adequate system equilibration.

③ Maintenance: Monitor column contamination and electrode status; regenerate/clean according to specifications to ensure long-term stability.

(3) Advantages/Limitations and Applicability

① Advantages: No derivatization required; high selectivity and sensitivity; suitable for trace sugar analysis.

② Limitations: Higher instrument and maintenance costs; stringent requirements for eluent and system cleanliness.

③ Use cases: Low-abundance/trace sugars, high-demand compositional profiling, and complex plant matrices.

2.2 Capillary Electrophoresis (CE)

(1) Principle

Sugar components are separated based on differences in electrophoretic mobility under a high-voltage electric field. Because sugars have low charge density, separation and detection are often enhanced via micellar electrokinetic chromatography (MEKC) with surfactants or via derivatization to introduce charged/fluorescent groups. Detectors may include UV, LIF, or MS.

(2) Key Workflow Notes

① Sample pretreatment: Deproteinization, decolorization/dephenolization, concentration, etc., to improve separation and detection stability.

② Separation conditions: Strictly control buffer pH, ionic strength, temperature, and voltage to improve reproducibility.

③ Detection strategy: LIF typically requires derivatization; MS coupling requires consideration of volatile buffer systems.

(3) Advantages/Limitations and Applicability

① Advantages: Fast analysis, very low sample consumption, high resolution; suitable for micro-samples and rapid screening.

② Limitations: Reproducibility is sensitive to operational conditions; UV sensitivity is limited; LIF depends on derivatization.

③ Use cases: Sample-limited studies, rapid separations, or methodological exploration.

2.3 Spectroscopic Methods

2.3.1 Near-Infrared Spectroscopy (NIRS)

(1) Principle

Using characteristic NIR absorption information of sugars, chemometric modeling (e.g., PLS) is applied to establish quantitative relationships between spectra and concentrations, enabling rapid prediction.

(2) Key Workflow Notes

① Sample consistency: Grinding size, moisture status, and packing method must be consistent.

② Model building: Use a sufficiently broad calibration set; perform cross-validation and external validation.

③ Model maintenance: Update models periodically to prevent drift due to changes in cultivar, season, and matrix.

(3) Advantages/Limitations and Applicability

① Advantages: Rapid, non-destructive, suitable for online/batch testing and process monitoring.

② Limitations: Strongly dependent on model quality; sensitive to matrix factors such as water and protein; limited generalization across scenarios.

③ Use cases: High-throughput screening, processing QC, and on-site rapid assessment.

2.3.2 Raman Spectroscopy

(1) Principle

Qualitative and quantitative analysis is based on Raman scattering peaks corresponding to molecular vibrational modes of sugars; applicable to in situ and micro-region analysis.

(2) Advantages/Limitations and Applicability

① Advantages: Non-destructive, relatively simple pretreatment, supports in situ detection.

② Limitations: Lower sensitivity; prone to fluorescence background interference; higher instrument cost.

③ Use cases: Applications requiring spatial distribution information, in situ identification, or microscopy-coupled analysis.

III. Emerging Detection Technologies

Emerging technologies promote miniaturization, real-time measurement, and intelligent analytics, particularly for field monitoring, online control, or rapid analysis of ultra-small samples. Many approaches remain in iterative development; standardization and comparability are key to broader adoption.

3.1 Biosensor-Based Methods

(1) Principle

Recognition elements such as enzymes, antibodies, or nucleic-acid aptamers are immobilized on electrodes or optical platforms. Target sugar binding induces electrical or optical signal changes for quantification; a typical example is the glucose oxidase electrochemical sensor.

(2) Advantages/Limitations and Applicability

① Advantages: High specificity and sensitivity, fast response, suitable for real-time online measurement.

② Limitations: Recognition element stability is affected by temperature, pH, and long-term storage; currently better suited for single-target sugars and less capable of multi-component profiling.

③ Use cases: Real-time monitoring of a single sugar, online process control, and prototype development for on-site testing.

3.2 Microfluidic Chip Technologies

(1) Principle

Extraction/cleanup, separation, and detection units are integrated on a micro-scale chip, combined with electrophoresis, chromatography, or biosensing for rapid analysis, featuring low sample consumption and portability potential.

(2) Advantages/Limitations and Applicability

① Advantages: Very low sample consumption, fast analysis, high integration, and potential evolution into portable devices.

② Limitations: Complex fabrication/packaging; batch-to-batch consistency and reproducibility still need improvement.

③ Use cases: Field-testing device development, rapid integrated multi-parameter analysis, and exploration of new methodologies.

IV. Comparison of Detection Technologies and Application Selection

Detection Technology	Sensitivity	Specificity	Operational Complexity	Cost	Typical Application Scenarios
Phenol–sulfuric acid method	Medium	Low	Low	Low	Basic labs; rapid total sugar determination for large batches
DNS method	Medium	Medium	Low	Low	Reducing sugar determination and reducing/non-reducing sugar estimation
HPLC	Medium–High	High	Medium	Medium–High	Qualitative/quantitative multi-component sugars; research and quality testing
GC/GC–MS	High	High	High	Medium–High	Complex samples; trace multi-component sugars; enhanced identification
IC–PAD	High	High	Medium	High	Trace sugars; derivatization-free multi-component detection
NIRS	Medium	Medium	Low	High	High-throughput non-destructive testing; online monitoring (model-dependent)
Biosensors	High	High	Medium	Medium	Real-time online testing and on-site rapid testing for single sugars
Microfluidic chips	Medium–High (method-dependent)	Medium–High (method-dependent)	Medium–High	Medium–High	Portable/integrated detection R&D; rapid analysis with small samples

V. Aladdin-Related Products

Catalog No.	Product Name	Method Type	Primary Target	Typical Uses / Scenarios	Best-Fit Sample Type & Throughput	Selection Notes
P1507814	Plant Soluble Sugar Content Assay Kit (Anthrone, Micro Method)	Anthrone–sulfuric acid colorimetry (micro / microplate)	Total soluble sugars (reported as “total sugar” calculated using glucose, etc.)	① Soluble sugar accumulation under stress (drought/salt/low temperature); ② Screening of photosynthate allocation and carbon metabolism phenotypes; ③ Sugar-content comparison in fruits/tubers and other quality traits	Suitable for small sample amounts and large numbers of samples; commonly read on 96-well plates for batch testing	“Micro method” is preferred for high throughput and small volumes; suitable for quickly running large batches and comparing treatment groups
P1507813	Plant Soluble Sugar Content Assay Kit (Anthrone, Colorimetric Method)	Anthrone–sulfuric acid colorimetry (conventional cuvette)	Total soluble sugars	① Routine physiological index measurement and publication-ready data; ② Sugar-content comparison across tissues/developmental stages; ③ Teaching and basic lab routine quantification	Better for relatively sufficient sample amounts and medium sample numbers; typically measured by spectrophotometer cuvette	The conventional method is often more convenient for routine workflows; repeatability control is relatively straightforward; efficient for moderate batch sizes
P1507811	Plant Soluble Sugar Content Assay Kit (Phenol, Micro Method)	Phenol–sulfuric acid colorimetry (micro / microplate)	Total soluble sugars	① High-throughput screening of total sugar levels (treatments, cultivars, transgenic lines); ② Scenarios requiring reduced sample/reagent consumption; ③ Batch testing after field sampling	Suitable for small sample amounts and large numbers of samples; commonly used in microplate formats	Phenol and anthrone methods both target “total sugar”; differences are mainly in color chemistry and readout wavelength; micro formats emphasize throughput and sample saving
P1507806	Plant Soluble Sugar Content Assay Kit (Phenol, Colorimetric Method)	Phenol–sulfuric acid colorimetry (conventional cuvette)	Total soluble sugars	① Routine total sugar quantification across tissues (leaf/root/stem/fruit/seed/tuber, etc.); ② Quality evaluation and treatment-effect comparison; ③ “Total sugar background” indicator prior to chromatographic profiling	Better for relatively sufficient sample amounts and medium sample numbers; spectrophotometer cuvette measurement	Conventional cuvette workflows tend to be less sensitive to well-to-well variability than microplates; suitable when robust output is prioritized

Overall, selection of plant soluble sugar detection methods should be driven by the research objective. Colorimetric methods are appropriate for low-cost, high-throughput screening of total sugars or reducing sugars. HPLC, IC–PAD, and GC/GC–MS support high-confidence qualitative and quantitative multi-component profiling, with sensitivity and identification power strongly dependent on detectors and pretreatment strategies. NIRS, biosensors, and microfluidics emphasize non-destructive, online, and portable applications, but impose higher requirements on modeling, anti-interference capability, and standardization. In practice, define target metrics and matrix characteristics first, and then ensure accuracy and comparability through standardized pretreatment, appropriate standards/internal standards, and method validation.

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